Brain cancer visualise quality control
Daniel Brown
2024-06-17
TurboCapture-Seq Brain Cancer neurospheres
Recap
These are the first experiments where I use version 2 chemistry. Read 2 is now the barcode and UMI Read 1 is the cDNA. This was done to avoid reading through the TSO on Ilumina read 1
Test version 2 protocol with a biological appliation from Zac Moore of Brain Cancer lab https://au-mynotebook.labarchives.com/share/Piper_Research_Project/MzEuMjAwMDAwMDAwMDAwMDAzfDE3MTc2NS8yNC9UcmVlTm9kZS8zMzczNDM0NjE1fDc5LjE5OTk5OTk5OTk5OTk5
Check orientation on plate map representation
Orientation is correct when looking at library size and mouse counts.
Samples
p1 <- platetools::raw_map(data=tb$Cell_Line,
well=tb$Well,
plate=96) + scale_fill_Publication()
p2 <- platetools::raw_map(data=log(tb$sum+1),
well=tb$Well,
plate=96) +
ggtitle("Library Size")
p3 <- platetools::raw_map(data=tb$Day_Exposure,
well=tb$Well,
plate=96) +
ggtitle("Days exposure to drug")
p4 <- platetools::raw_map(data=tb$Storage,
well=tb$Well,
plate=96) +
ggtitle("Storage conditions") + scale_fill_Publication()
p1 + p2 + p3 + p4
Conditions
tb_fact <- tb
tb_fact$Day_Exposure <- as.factor(tb$Day_Exposure)
tb_fact$Dose_M <- as.factor(tb$Dose_M)
p1 <- platetools::raw_map(data=tb_fact$Species,
well=tb$Well,
plate=96) +
scale_fill_discrete("Species")
p2 <- platetools::raw_map(data=tb_fact$Day_Exposure,
well=tb$Well,
plate=96) +
scale_fill_discrete("Timepoint (days)")
p3 <- platetools::raw_map(data=tb_fact$Dose_M,
well=tb$Well,
plate=96) +
guides(fill=guide_legend(ncol=2)) +
scale_fill_discrete("Dose (M)")
p4 <- platetools::raw_map(data=tb_fact$Drug,
well=tb$Well,
plate=96) +
scale_fill_discrete("Drug")
p1 + p4 + p3 + p2
Quality control metrics by dose
The metrics go as one would expect with dose and time treated
Library size
tb$Day_Exposure <- as_factor(tb$Day_Exposure)
plt1 <- ggplot(tb,
aes(x = Dose_M, y= sum, colour=Day_Exposure)) +
geom_point() +
ylab("Library Size (UMIs)") +
xlab("TMZ (M)") +
scale_y_continuous(trans='log10') + scale_x_continuous(trans='log10') +
annotation_logticks(base = 10, sides = "bl") +
scale_colour_brewer(palette = "Dark2")
plt1
Investigate storage conditions
Evidence that storage at 4C is insufficient to freeze the biological effect of temozolomide on the library size. In general metrics are poorer for storage at 4C.
storage <- tb %>%
filter(Day_Exposure == 7) %>%
filter(Dose_M != 0.0000001) %>%
filter(Dose_M != 0.000001) %>%
filter(Dose_M != 0.00000316) %>%
filter(Dose_M != 0.000000316) %>%
filter(Dose_M != 0.0000316)
storage %>%
dplyr::count(Dose_M,Storage)Library size
plt1 <- ggplot(storage,
aes(x = Storage, y= sum, colour=Drug)) +
geom_jitter(width = 0.1) +
ylab("Library Size (UMIs)") +
xlab("Storage") +
scale_y_continuous(trans='log10') +
annotation_logticks(base = 10, sides = "l") +
scale_colour_brewer(palette = "Dark2")
plt1
Genes detected
plt2 <- ggplot(storage,
aes(x = Storage, y= detected, colour=Drug)) +
geom_jitter(width = 0.1) +
ylab("Genes detected") +
xlab("Storage") +
scale_colour_brewer(palette = "Dark2")
plt2
Mitochondrial percent
Further evidence that 4C storage does not inactivate Temozolomide effects.
plt3 <- ggplot(storage,
aes(x = Storage, y= subsets_Mito_percent, colour=Drug)) +
geom_jitter(width = 0.1) +
ylab("Mitochondrial %") + ylim(0,15) +
xlab("Storage") +
scale_colour_brewer(palette = "Dark2")
plt3
Session info
## R version 4.4.0 (2024-04-24)
## Platform: x86_64-pc-linux-gnu
## Running under: CentOS Linux 7 (Core)
##
## Matrix products: default
## BLAS: /stornext/System/data/apps/R/R-4.4.0/lib64/R/lib/libRblas.so
## LAPACK: /stornext/System/data/apps/R/R-4.4.0/lib64/R/lib/libRlapack.so; LAPACK version 3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## time zone: Australia/Melbourne
## tzcode source: system (glibc)
##
## attached base packages:
## [1] grid stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] scales_1.3.0 ggthemes_5.1.0
## [3] here_1.0.1 patchwork_1.2.0
## [5] platetools_0.1.7 scater_1.32.0
## [7] scuttle_1.14.0 lubridate_1.9.3
## [9] forcats_1.0.0 stringr_1.5.1
## [11] dplyr_1.1.4 purrr_1.0.2
## [13] readr_2.1.5 tidyr_1.3.1
## [15] tibble_3.2.1 ggplot2_3.5.1
## [17] tidyverse_2.0.0 SingleCellExperiment_1.26.0
## [19] SummarizedExperiment_1.34.0 Biobase_2.64.0
## [21] GenomicRanges_1.56.0 GenomeInfoDb_1.40.0
## [23] IRanges_2.38.0 S4Vectors_0.42.0
## [25] BiocGenerics_0.50.0 MatrixGenerics_1.16.0
## [27] matrixStats_1.3.0
##
## loaded via a namespace (and not attached):
## [1] tidyselect_1.2.1 viridisLite_0.4.2
## [3] farver_2.1.2 vipor_0.4.7
## [5] viridis_0.6.5 fastmap_1.2.0
## [7] digest_0.6.35 rsvd_1.0.5
## [9] timechange_0.3.0 lifecycle_1.0.4
## [11] magrittr_2.0.3 compiler_4.4.0
## [13] rlang_1.1.3 sass_0.4.9
## [15] tools_4.4.0 utf8_1.2.4
## [17] yaml_2.3.8 knitr_1.46
## [19] labeling_0.4.3 S4Arrays_1.4.0
## [21] DelayedArray_0.30.1 RColorBrewer_1.1-3
## [23] abind_1.4-5 BiocParallel_1.38.0
## [25] withr_3.0.0 fansi_1.0.6
## [27] beachmat_2.20.0 colorspace_2.1-0
## [29] cli_3.6.2 rmarkdown_2.26
## [31] crayon_1.5.2 generics_0.1.3
## [33] rstudioapi_0.16.0 httr_1.4.7
## [35] tzdb_0.4.0 DelayedMatrixStats_1.26.0
## [37] ggbeeswarm_0.7.2 cachem_1.1.0
## [39] zlibbioc_1.50.0 parallel_4.4.0
## [41] XVector_0.44.0 vctrs_0.6.5
## [43] Matrix_1.7-0 jsonlite_1.8.8
## [45] BiocSingular_1.20.0 hms_1.1.3
## [47] BiocNeighbors_1.22.0 ggrepel_0.9.5
## [49] irlba_2.3.5.1 beeswarm_0.4.0
## [51] jquerylib_0.1.4 glue_1.7.0
## [53] codetools_0.2-20 stringi_1.8.4
## [55] gtable_0.3.5 UCSC.utils_1.0.0
## [57] ScaledMatrix_1.12.0 munsell_0.5.1
## [59] pillar_1.9.0 htmltools_0.5.8.1
## [61] GenomeInfoDbData_1.2.12 R6_2.5.1
## [63] sparseMatrixStats_1.16.0 rprojroot_2.0.4
## [65] evaluate_0.23 lattice_0.22-6
## [67] highr_0.10 bslib_0.7.0
## [69] Rcpp_1.0.12 gridExtra_2.3
## [71] SparseArray_1.4.3 xfun_0.44
## [73] pkgconfig_2.0.3